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Marx, W.; Bornmann, L.: On the problems of dealing with bibliometric data (2014)
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- 18. 3.2014 19:13:22
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Antos, G.: Wie Sprache Entscheidungen (vor)prägt : zum Einfluss und zur Rhetorik kollektiver Selbsttäuschungen (2014)
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- 6. 7.2014 18:22:33
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Shaw, R.; Golden, P.; Buckland, M.: Using linked library data in working research notes (2015)
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- 15. 1.2016 19:22:28
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Foskett, D.J.: Systems theory and its relevance to documentary classification (2017)
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- 6. 5.2017 18:46:22
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Bursa, O. et al.: Enriching preferences using DBpedia and Wordnet (2016)
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- Metadata and semantics research: 10th International Conference, MTSR 2016, Göttingen, Germany, November 22-25, 2016, Proceedings. Eds.: E. Garoufallou
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Ceynowa, K.: Research Library Reloaded? : Überlegungen zur Zukunft der geisteswissenschaftlichen Forschungsbibliothek (2018)
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- Date
- 1. 2.2019 12:50:22
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- a
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Hauer, M.: Tiefenindexierung im Bibliothekskatalog : 17 Jahre intelligentCAPTURE (2019)
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- B.I.T.online. 22(2019) H.2, S.163-166
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Xiong, C.: Knowledge based text representations for information retrieval (2016)
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- Abstract
- The successes of information retrieval (IR) in recent decades were built upon bag-of-words representations. Effective as it is, bag-of-words is only a shallow text understanding; there is a limited amount of information for document ranking in the word space. This dissertation goes beyond words and builds knowledge based text representations, which embed the external and carefully curated information from knowledge bases, and provide richer and structured evidence for more advanced information retrieval systems. This thesis research first builds query representations with entities associated with the query. Entities' descriptions are used by query expansion techniques that enrich the query with explanation terms. Then we present a general framework that represents a query with entities that appear in the query, are retrieved by the query, or frequently show up in the top retrieved documents. A latent space model is developed to jointly learn the connections from query to entities and the ranking of documents, modeling the external evidence from knowledge bases and internal ranking features cooperatively. To further improve the quality of relevant entities, a defining factor of our query representations, we introduce learning to rank to entity search and retrieve better entities from knowledge bases. In the document representation part, this thesis research also moves one step forward with a bag-of-entities model, in which documents are represented by their automatic entity annotations, and the ranking is performed in the entity space.
This proposal includes plans to improve the quality of relevant entities with a co-learning framework that learns from both entity labels and document labels. We also plan to develop a hybrid ranking system that combines word based and entity based representations together with their uncertainties considered. At last, we plan to enrich the text representations with connections between entities. We propose several ways to infer entity graph representations for texts, and to rank documents using their structure representations. This dissertation overcomes the limitation of word based representations with external and carefully curated information from knowledge bases. We believe this thesis research is a solid start towards the new generation of intelligent, semantic, and structured information retrieval.
- Content
- Submitted in partial fulfillment of the requirements for the degree of Doctor of Philosophy in Language and Information Technologies. Vgl.: https%3A%2F%2Fwww.cs.cmu.edu%2F~cx%2Fpapers%2Fknowledge_based_text_representation.pdf&usg=AOvVaw0SaTSvhWLTh__Uz_HtOtl3.
-
Gömpel, R.; Junger, U.; Niggemann, E.: Veränderungen im Erschließungskonzept der Deutschen Nationalbibliothek (2011)
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- Dialog mit Bibliotheken. 22(2010) H.1, S.20-22
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- a
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Schultz, S.: ¬Die eine App für alles : Mobile Zukunft in China (2016)
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- Date
- 22. 6.2018 14:22:02
- Source
- http://www.spiegel.de/wirtschaft/unternehmen/messenger-apps-wie-china-die-mobile-zukunft-erfindet-a-1071815.html
-
Guidi, F.; Sacerdoti Coen, C.: ¬A survey on retrieval of mathematical knowledge (2015)
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- Abstract
- We present a short survey of the literature on indexing and retrieval of mathematical knowledge, with pointers to 72 papers and tentative taxonomies of both retrieval problems and recurring techniques.
- Date
- 22. 2.2017 12:51:57
- Type
- a
-
Kopácsi, S. et al.: Development of a classification server to support metadata harmonization in a long term preservation system (2016)
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- Source
- Metadata and semantics research: 10th International Conference, MTSR 2016, Göttingen, Germany, November 22-25, 2016, Proceedings. Eds.: E. Garoufallou
- Type
- a
-
Sojka, P.; Liska, M.: ¬The art of mathematics retrieval (2011)
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- Abstract
- The design and architecture of MIaS (Math Indexer and Searcher), a system for mathematics retrieval is presented, and design decisions are discussed. We argue for an approach based on Presentation MathML using a similarity of math subformulae. The system was implemented as a math-aware search engine based on the state-ofthe-art system Apache Lucene. Scalability issues were checked against more than 400,000 arXiv documents with 158 million mathematical formulae. Almost three billion MathML subformulae were indexed using a Solr-compatible Lucene.
- Content
- Vgl.: DocEng2011, September 19-22, 2011, Mountain View, California, USA Copyright 2011 ACM 978-1-4503-0863-2/11/09
- Date
- 22. 2.2017 13:00:42
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- a
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Paul-Hus, A.; Desrochers, N.; Rijcke, S.de; Rushforth, A.D.: ¬The reward system of science (2017)
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- Date
- 20. 1.2015 18:30:22
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Calì, A. et al.: Processing keyword queries under access limitations (2016)
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